Data integration is a general concept used in the computing life. Actually, it’s everywhere to facilitate your life and make better service. For professionals, data integration is a must-to-learn technique and you can will be surprised by this amazing technique. Come to this post on MiniTool and know more about it
What Is Data Integration?
What is data integration? To make this easy to understand, we can conclude the whole complicated process as “combining”. During the data integration, the data residing in disparate sources will be consolidated into a single dataset and the users will receive a unifies view of them with consistent access and delivery of data.
As a result, the collected data will be comprehensive and reliable and that will be available for business analysis and reporting.
That will meet the information needs of all applications and business processes. This process is much important to be applied in all kinds of situations, such as commercial and scientific fields.
So, as for its useful function, how to achieve that? Some data integration architects develop specific programs or platforms, with a variety of data integration techniques, to achieve the process for connecting and routing data from source systems to target systems.
The referred techniques are as follows.
ETL (Extract, Transform and Load) – data is extracted, transformed, and loaded into an output data container and in the Transform phase, the data will be cleaned, sanitized, and scrubbed.
It has been introduced on MiniTool and you can read this one: What Is ETL (Extract, Transform, Load) – Definition & Guide.
ELT (Extract, Load and Transform) – a data integration process for transferring raw data from a source server to a data system.
CDC (Change Data Capture) – it used to identify and capture changes made to data in a database and then deliver the changes to a targeting system in real time.
Data Replication – it copies data from one place to another one in real time in order to improve data accessibility across a network.
What is data replication? How many data replication types are there? How to perform data replication to protect from data loss in case of computer crashes?
Data Virtualization – it allows a program to retrieve and manage data without technical details about the data, reducing the risk of data errors.
Streaming Data Integration – it refers to integrating data sources in real time to provide up-to-the-minute information.
Data Integration Tools
As the name implies, data integration tools are specially designed to perform data integration process, such as mapping, transformation, and cleansing.
There are some types of data integration tools you can refer to.
On-premise Data Integration
On-premises refers to IT infrastructure hardware and software applications that are hosted on-site, while on-premise data integration software allows businesses to unify data from disparate on-premise sources within a company in various formats. It can provide the functionality to cleanse, monitor, and transform data.
Cloud-based Data Integration
It can respond to the need to share data among cloud-based applications and to unify information components, unifying data from different sources where at least one endpoint is a cloud source into a more useful view.
Open-source Data Integration
There are many great open-source data integration programs that can enable anyone to leverage a robust and production-level integration in a record amount of time, all without sacrificing the customizability of the connectors.
Proprietary Data Integration
Different from Open-source Data Integration tools, it is built to cater very well to specific business use cases. This kind of tools are mature and full featured and you will gain more accurate data via it.
Why Is Data Integration Important?
First of all, this process is used to provide enormous datasets after a series of accurate and comprehensive analysis. These data can benefit businesses and customers to gain data enrichment and real time information delivery.
For example, data integration has been widely used in managing business and customer data. For the businesses’ interest, data integration can support enterprise reporting, business intelligence, and advanced enterprise analytics via its data warehouses.
For customer data integration, it will show a general picture of KPI, financial risks, and supply chain operations for data analysts.
Apart from the computing industry, in the healthcare industry, doctors can use data integration to collect useful information from different patients and hospitals, forming a comprehensive picture of the disease.
After reading this article, you may have figured out what data integration is. On MiniTool, more information will be shared here and you can go and learn what you are interested in. If you have any question, please leave your message.